Instructions to use chen70335/longformer-base-4096-with-sampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chen70335/longformer-base-4096-with-sampling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chen70335/longformer-base-4096-with-sampling")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chen70335/longformer-base-4096-with-sampling") model = AutoModelForSequenceClassification.from_pretrained("chen70335/longformer-base-4096-with-sampling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train.csv from chen70335/longformer-base-4096-with-sampling: direct link, hf CLI and curl.
- Browser
- Download file 15.7 MB
-
https://huggingface.co/chen70335/longformer-base-4096-with-sampling/resolve/main/train.csv
- Command line
-
hf download hf://chen70335/longformer-base-4096-with-sampling/train.csv
-
curl -L -o train.csv https://huggingface.co/chen70335/longformer-base-4096-with-sampling/resolve/main/train.csv
15.7 MB
- Xet hash:
- 490eca2c72e68b07817bba869c68f197644d692558228bef75fb06ad9f788bc1
- Size of remote file:
- 15.7 MB
- SHA256:
- 3648097d79adca4196171fa701d85c5ac9d303a6a785966e61eb432d7ec80c5f
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